proposal

Ziqi Tang

Introduction to problem/question

As Earth’s population grows, remote sensing of nighttime light emissions offers a unique perspective for investigations into some of these human behaviors. China’s economy has developed rapidly in recent years. However, there are gaps in urban construction and economic development in different regions.

Problem / Question

What are the characteristics of the distribution and change of nighttime value in China from 2000 to 2017?

Inspiring Examples

Example 1

I found this graphic easy to understand the CO2 emissions in different countries. This type of graphic could be used to reflect the distribution of night light in each province of China.

Example 2

I found this graphic easy to understand the changes in the numbers of monthly active users in different countries. This type of graphic could be used to reflect the changes in nighttime value in each province from 2000 to 2017.

Example 3

This composite image shows the continental U.S. at night. The relationship between metropolitan agglomerations can be felt more naturally on a raster map.

Proposed data sources

An extended time-series (2000-2018) of global NPP-VIIRS-like nighttime light data

Proposed methods

1.read_xlsx: read data in Excel

2.filter&dplyr: select the maximum and mean value from the nighttime data

3.ggplot: plot the nighttime value on the map

Expected results

1. The changes in the nighttime value of different provinces in China from 2000 to 2017

2. The distribution of nighttime value in China